Classification of leukemia gene expression profiles based on multivariant optimization algorithm

Yajie,Xinling Shi,Changxing Gou,Baolei Li,Qinhu Zhang, L V Danjv,Yunchao Huang

Bioelectronics and Bioinformatics（2014）

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摘要

Classification of leukemia samples based on gene expression profiles has been proved an efficient way. Large numbers of intelligence algorithms have been exploited based on this purpose. However, few of them display stable and accurate performance for both low and high gene dimensionalities. Still none of them could keep the history information of optimization. Here, a classification algorithm based on the novel multivariant optimization algorithm (MOA) is proposed. Leukemia gene expression profiles with different dimensionalities are used for validation. The particle swarm optimization (PSO) and the two-layer particle swarm optimization (TLPSO) algorithm are used for comparison. The MOA shows stable and relatively accurate classification performance and could be used as an effective classification algorithm for gene expression profiles.

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关键词

bioinformatics,blood,cancer,genetics,genomics,learning (artificial intelligence),particle swarm optimisation,intelligence algorithms,leukemia gene expression profile classification,multivariant optimization algorithm,two-layer particle swarm optimization algorithm,moa,classification,gene,leukemia,particle swarm optimization,classification algorithms,gene expression,prediction algorithms,learning artificial intelligence,optimization,accuracy

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